Pricing and Simulation for Extreme Flood Catastrophe Bonds

With global climate change, the extreme flood disasters which are characterized with low frequency but huge economic losses occur more frequently. The management of the extreme flood disasters mainly depends on the administrative means of the governments at all levels in China. When the extreme flood occurs, the government financial aid and the social donation can be used to compensate the catastrophe losses, but these compensations account for only a small part of the catastrophe losses. Therefore, it is very urgent to disperse the flood catastrophe risk by social system. The catastrophe risk securitization bridges the capital market and the insurance market and can effectively transfer the catastrophe risk to the capital market. The catastrophe bond is an effective risk dispersion mode and the pricing of catastrophe bonds is the core issue of implementing catastrophe bonds. However, the research about the design and the pricing of extreme flood catastrophe bond is scarce. In this study, a kind of one-year extreme flood catastrophe bond was designed and simulations on the pricing according to the extreme flood data in China during 1961 to 2009 with quantitative analysis method were done, combined with the non-life insurance actuarial method and Wang-double-factor model. The results show that price of catastrophe bond is increasing with the increase of the value for triggering points and reducing when the ratio that corporation confiscates the capital and the interest of catastrophe bond enlarges. Some reasons were discussed to account for the results. The results show that the method is effective and can provide some guidance for the pricing of extreme flood catastrophe bonds.     

Challenges of recycled water pricing

Recycled water has posed new challenges for conventional water supply and wastewater provision models, as it interconnects different related services. The reclaimed water sector faces the arduous task of setting specific pricing policies since rules for potable water and wastewater charges may not be appropriate for it. This article addresses a review of current challenges in pricing policies for recycled water based on case studies available worldwide, highlighting the most common tariff structures in use and the principles applied, providing a guideline for recycled water pricing based on the barriers, drivers, and practices found around the global experiences and academic literature. The results show that different tariff structures are adopted based on local socioeconomic factors and water authorities’ objectives. We conclude that the local environmental conditions, the institutional arrangement, technical and economic specificities are influence factors that decision-makers should consider when setting recycled water charges.     

基于模糊多属性群决策的工程交易模式选择研究

工程项目是国家进行实体投资的主要方式,而工程交易模式对工程项目能否成功实施起着决定性作用。为了使业主方能够选择出更加恰当的工程交易模式,文章对影响工程交易模式的影响因素进行了归纳总结,构建了工程交易模式决策指标体系。由于业主在进行工程交易模式选择时涉及的因素非常多且十分复杂,因此工程交易模式的选择是一个多属性的决策问题。文章通过运用熵权法及模糊多属性决策理论,建立了模糊多属性群决策模型,并用实例对该模型进行了验证,确保其有效性,最终为业主方提供了更加科学、合理、实用的工程交易模式的决策方法。     

重大工程投资项目绿色冲突的网络特征及其风险化解——基于2-模网络与“中间人”角色视角

 随着绿色发展理念深入人心,重大工程投资项目绿色冲突愈发强烈,寻求有效手段化解绿色冲突是重大工程投资项目成功建设运营的重要支撑。论文从冲突主体和行为因素之间的影响力出发,强调绿色冲突中冲突主体与冲突行为的联动作用,构建“利益相关者-环境风险因素”2-模网络,选取2000-2018年中国发生的53起重大工程投资项目绿色冲突案例,以“中间人”角色为抓手分析重大工程投资项目绿色冲突的特征及关键环节,从而化解绿色冲突带来的风险。研究结果表明,冲突网络密度为0.457 1,内部黏性较强;当地政府办公室、环境保护部门、当地民众、媒体等利益相关者不仅在绿色冲突网络中中心性最高,有最强影响力,而且向群体内外交流的角色作用也最强,有最为畅通的信息沟通渠道和强烈的信息交流意愿。因此必须建立环境风险预警系统,把解决关键环境问题与畅通信息沟通渠道同时放于化解绿色冲突的首位。     

Information systems evaluation: navigating through the problem domain

Information systems (IS) make it possible to improve organizational efficiency and effectiveness, which can provide competitive advantage. There is, however, a great deal of difficulty reported in the normative literature when it comes to the evaluation of investments in IS, with companies often finding themselves unable to assess the full implications of their IS infrastructure. Although many of the savings resulting from IS are considered suitable for inclusion within traditional accountancy frameworks, it is the intangible and non-financial benefits, together with indirect project costs that complicate the justification process. In exploring this phenomenon, the paper reviews the normative literature in the area of IS evaluation, and then proposes a set of conjectures. These were tested within a case study to analyze the investment justification process of a manufacturing IS investment. The idiosyncrasies of the case study and problems experienced during its attempts to evaluate, implement, and realize the holistic implications of the IS investment are presented and critically analyzed. The paper concludes by identifying lessons learnt and thus, proposes a number of empirical findings for consideration by decision-makers during the investment evaluation process.     

Spillovers between oil and stock returns in the US energy sector: Does idiosyncratic information matter?

This paper investigates the inter-connectedness between WTI oil price returns and the returns of listed firms in the US energy sector. Specifically, we focus on the issue of whether firm-level idiosyncratic information matters. A generalised dynamic factor model is used to separate common components from idiosyncratic components in these energy stocks. Systemic connectedness is then estimated following Diebold and Yilmaz (2014). Our empirical results demonstrate the important role of industrial-level common information in understanding the oil–stock relationship. A number of interesting points include: the US energy sector is the net contributor to WTI price changes, but the effect is mainly driven by industrial-level common information; the oil and gas industry dominates other industries in the energy sector; the dynamic analysis shows that although idiosyncratic information is mostly independent of oil shocks, individual energy stock returns do respond to WTI price movements.     

A method for analyzing pollution control policies: Application to SO2 emissions in China

Market-based pollution control mechanisms such as pollution levy and cap and trade have received increasing attention from both academics and practitioners. A good understanding of the optimal pollution price under these mechanisms is a premise for regulators to make sound pollution control policies. In this paper, we propose a method for deriving the optimal pollution price for a given pollution target. This method consists of two steps that integrate cost function estimation and market equilibrium analysis: First, historical data is used to estimate the pollution abatement cost functions of the polluters; second, market models are used to solve the equilibrium pollution price under each control mechanism. For illustration, we apply the method to investigate SO₂ emission control policies in China, using a dataset of SO₂ emissions and abatement costs from three major industry sectors (Electricity, Gas, and Water Supply; Manufacturing; and Mining). Our analysis shows that the optimal levy rate is significantly higher than the actual rate adopted by the Chinese government. For example, the optimal levy rate should be 4.92 RMB/kg, while the actual rate is 1.26 RMB/kg in 2010. As a result, the actual emission structure is much less efficient: The overall cost savings would be 49.7% for all three sectors during 2006–2010 if the optimal emission structure is achieved. These findings have useful policy implications for the Chinese government. In addition, the method may be applied to analyze control policies at different aggregate levels (for example, provincial economies) or for other pollutants (for example, CO₂ and chemical oxygen demand).     

Hierarchical learning using deep optimum-path forest

Bag-of-Visual Words (BoVW) and deep learning techniques have been widely used in several domains, which include computer-assisted medical diagnoses. In this work, we are interested in developing tools for the automatic identification of Parkinson’s disease using machine learning and the concept of BoVW. The proposed approach concerns a hierarchical-based learning technique to design visual dictionaries through the Deep Optimum-Path Forest classifier. The proposed method was evaluated in six datasets derived from data collected from individuals when performing handwriting exams. Experimental results showed the potential of the technique, with robust achievements.     

Measuring consensus in a preference-approval context

We consider measuring the degree of homogeneity for preference-approval profiles which include the approval information for the alternatives as well as the rankings of them. A distance-based approach is followed to measure the disagreement for any given two preference-approvals. Under the condition that a proper metric is used, we propose a measure of consensus which is robust to some extensions of the ordinal framework. This paper also shows that there exists a limit for increasing the homogeneity level in a group of individuals by simply replicating their preference-approvals.     

基于 BIM 的 EPC 项目价值增值研究

BIM 在发达国家广泛应用的实践经验表明能有效提高项目建设的生产效率。基于 BIM 和价值链理论，探讨 BIM 理念及相关技术在 EPC 项目价值链的各增值环节的重要作用，提出以 BIM 为基础，对 EPC 项目建设各环节的活动进行强化以提高项目质量和生产效率，对设计采购施工并行建设优化降低项目成本，为实现 EPC 项目价值增值提供手段和途径，也为业主、总承包商和其他利益相关方更好地创造价值和获取利润奠定基础。